Test baynes_sound_agrif Module¶
Render figure object produced by the nowcast.figures.research.baynes_sound_agrif module.
Set-up and function call replicates as nearly as possible what is done in the nowcast.workers.make_plots worker
to help ensure that the module will work in the nowcast production context.
This notebook must be run in a
Nowcast Figures Development Environment
so that all of the necessary dependency packages are installed.
Also, it must be run on a workstation that has the Salish Sea Nowcast system /results/ parition mounted.
# reload lets us pull in changes from modules that we edit
from importlib import reload
from pathlib import Path
import arrow
from nowcast.figures.research import baynes_sound_agrif
import io
import yaml
%matplotlib inline
The bits of config/nowcast.yaml that are required:
config = '''
figures:
dataset URLs:
bathymetry: https://salishsea.eos.ubc.ca/erddap/griddap/ubcSSnBathymetryV17-02
3d phys tracer fields: https://salishsea.eos.ubc.ca/erddap/griddap/ubcSSg3DTracerFields1hV17-02
3d bio tracer fields: https://salishsea.eos.ubc.ca/erddap/griddap/ubcSSg3DBiologyFields1hV17-02
results archive:
nowcast-agrif: /results/SalishSea/nowcast-agrif/
run types:
nowcast-agrif:
sub-grid bathymetry: /results/nowcast-sys/grid/subgrids/BaynesSound/bathymetry_201702_BS.nc
'''
config = yaml.load(io.StringIO(config))
The bits that the make_plots worker must provide:
run_type = 'nowcast-agrif'
run_date = arrow.get('2018-09-03')
ddmmmyy = run_date.format('DDMMMYY').lower()
yyyymmdd = run_date.format('YYYYMMDD')
agrif_results_dir = Path(config['results archive'][run_type], ddmmmyy)
ss_tracers_path = agrif_results_dir/'BaynesSoundSurface_grid_T.nc'
bs_phys_path = agrif_results_dir/f'1_SalishSea_1h_{yyyymmdd}_{yyyymmdd}_grid_T.nc'
bs_bio_path = agrif_results_dir/f'1_SalishSea_1h_{yyyymmdd}_{yyyymmdd}_ptrc_T.nc'
ss_grid_url = config['figures']['dataset URLs']['bathymetry']
bs_grid_path = Path(config['run types'][run_type]['sub-grid bathymetry'])
Render the Figure¶
The %%timeit cell magic lets us keep an eye on how log the figure takes to process.
Setting -n1 -r1 prevents it from processing the figure more than once
as it might try to do to generate better statistics.
%%timeit -n1 -r1
reload(baynes_sound_agrif)
# Make figure
fig = baynes_sound_agrif.make_figure(
ss_tracers_path, bs_phys_path, bs_bio_path, run_date, ss_grid_url, bs_grid_path,
)
/media/doug/warehouse/conda_envs/nowcast-fig-dev/lib/python3.6/site-packages/numpy/ma/core.py:6385: MaskedArrayFutureWarning: In the future the default for ma.minimum.reduce will be axis=0, not the current None, to match np.minimum.reduce. Explicitly pass 0 or None to silence this warning. return self.reduce(a) /media/doug/warehouse/conda_envs/nowcast-fig-dev/lib/python3.6/site-packages/numpy/ma/core.py:6385: MaskedArrayFutureWarning: In the future the default for ma.maximum.reduce will be axis=0, not the current None, to match np.maximum.reduce. Explicitly pass 0 or None to silence this warning. return self.reduce(a)
4.11 s ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)
